The present invention, in some embodiments thereof, relates to a system and a method for contextual search and, more particularly, but not exclusively, to a system and a method for discovering data according to contextual relation.
The emergence of the information age has created a wealth of information that is available electronically. Unfortunately, much of this information is often inaccessible to individuals and data mining systems because they do not know where to look for it or if they do know where to look, the information may not be found efficiently, inter alia because of the large amounts of information and/or because they do not know when is the right moment to look.
One common technique, implemented by traditional keyword search engines, matches words expected to found in a set of documents through pattern matching techniques. Thus, the more that is known in advance about the documents including their content, format, layout, etc., the better the search terms that may be provided to elicit a more accurate result. Data is searched and results are generated based on matching one or more words or terms that are designated as a query. Results such as documents are returned when they contain a word or term that matches all or a portion of one or more keywords that were submitted to the search engine as the query. Some keyword search engines additionally support the use of modifiers, operators, or a control language that specifies how the keywords should be combined when performing a search. For example, a query might specify a date filter to be used to filter the returned results. In many traditional keyword search engines, the results are returned ordered, based on the number of matches found within the data. For example, a keyword search against Internet websites typically returns a list of sites that contain one or more of the submitted keywords, with the sites with the most matches appearing at the top of the list. Accuracy of search results in these systems is thus presumed to be associated with frequency of occurrence.
During the last years, a number of systems and methods which are based on contextual and semantic maps have been developed. For example, U.S. Patent Application No. 2007/0260598 published on Nov. 8, 2007, provides search engine methods and systems for generating highly personalized and relevant search results based on the context of a user's search constraint and user characteristics. In an embodiment, upon receipt of a user's search constraint, the method determines all semantic variations for each word within the user search constraint. Additionally, topics may be determined within the user constraint. For each unique word and topic within the user search constraint, possible contexts are determined. A matrix of feasible context scenarios is established. Each context scenario is ranked to determine the most likely context scenario for which the user search constraint relates based on user characteristics. In one embodiment, the weighting used to rank the contexts is based on previous user searches and/or knowledge of their interests. Search results associated with the highest ranking context are provided to the user, along with topics associated with lower ranked contexts.
Another example is provided in U.S. Patent Application No. 2007/0156669 published on Jul. 5, 2007 that describes methods and systems for extending keyword searching techniques to syntactically and semantically annotated data are provided. Example embodiments provide a syntactic query engine (“SQE”) that parses, indexes, and stores a data set as an enhanced document index with document terms as well as information pertaining to the grammatical roles of the terms and ontological and other semantic information. In one embodiment, the enhanced document index is a form of term-clause index that indexes terms and syntactic and semantic annotations at the clause level. The enhanced document index permits the use of a traditional keyword search engine to process relationship queries as well as to process standard document level keyword searches.